10 citations · 28 across the 14 of their papers we have counts for
15 papers
ContextGNN: Beyond Two-Tower Recommendation Systems
Yiwen Yuan, Zecheng Zhang, Xinwei He +10
Recommendation systems predominantly utilize two-tower architectures, which evaluate user-item rankings through the inner product of their respective embeddings. However, one key l…
Personalized Binomial DAGs Learning with Network Structured Covariates
Boxin Zhao, Weishi Wang, Dingyuan Zhu +5
The causal dependence in data is often characterized by Directed Acyclic Graphical (DAG) models, widely used in many areas. Causal discovery aims to recover the DAG structure using…
PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce
Xiaowen Shi, Fan Yang, Ze Wang +6
Re-ranking draws increased attention on both academics and industries, which rearranges the ranking list by modeling the mutual influence among items to better meet users' demands.…
Task Aligned Meta-learning based Augmented Graph for Cold-Start Recommendation
Yuxiang Shi, Yue Ding, Bo Chen +4
The cold-start problem is a long-standing challenge in recommender systems due to the lack of user-item interactions, which significantly hurts the recommendation effect over new u…
Deep Page-Level Interest Network in Reinforcement Learning for Ads Allocation
Guogang Liao, Xiaowen Shi, Ze Wang +5
A mixed list of ads and organic items is usually displayed in feed and how to allocate the limited slots to maximize the overall revenue is a key problem. Meanwhile, modeling user…
Extracting Attentive Social Temporal Excitation for Sequential Recommendation
Yunzhe Li, Yue Ding, Bo Chen +5
In collaborative filtering, it is an important way to make full use of social information to improve the recommendation quality, which has been proved to be effective because user…